It is often desirable to determine the impact of environmental effects on the operation of electrical devices, and in some cases to counteract such effects. For example, active noise cancellation (ANC) is a desirable feature in earpieces. (As used herein, “earpiece” encompasses any sound reproduction device worn over, on or in a user's ear, including headsets, headphones, or earbuds.) The effect of noise cancellation is to suppress ambient noise without changing an audio signal applied to the earpiece, so that the user is subjected to a lower level of the ambient noise, and the user's listening experience is thus improved. Noise cancellation is particularly useful where the level of ambient noise is substantial, for example in airplanes, trains and other similar environments.
There are three well-known types of ANC. In “feedforward” ANC, a microphone is placed away from the earpiece, and receives the ambient noise before the user does. In “feedback” embodiments of ANC, a microphone is placed near the earpiece, or even in the earpiece itself, and thus receives the ambient noise in substantially the same way as the user does. Those of skill in the art will be aware of the limitations of both feedforward and feedback ANC, and of the use of “hybrid” embodiments of ANC that include both feedforward and feedback techniques in an effort to achieve better noise cancellation.
The present application concerns feedback ANC. In feedback ANC, the microphone near or in the earpiece receives the ambient noise, resulting in an ambient noise signal. A signal that is an inverted copy of the ambient noise signal is added to the intended audio signal such that the addition of the inverted copy in the desired audio program cancels, to some degree, the perceived ambient noise. Thus, additional noise, i.e., the inverted copy, is added to the desired audio program to cancel the ambient noise, and the user perceives that the ambient noise level is lower.
The amplitude and phase of the inverted noise-cancelling signal is preferably selected so as to optimize this perceived reduction of ambient noise. This is typically accomplished by the use of an adaptive feedback loop of some kind; in some embodiments, a Finite Impulse Response Filter (FIR) is configured using a Least Mean Squares (LMS) algorithm to optimally remove the noise. Such techniques are well known in the art.
However, the need for a microphone to detect the ambient noise results in limitations on the ability to successfully perform active noise cancellation. One is that the proximity of the microphone and the earpiece driver is critical to performance; the speed of sound in air means that even small differences in position between the microphone and the earpiece transducer can cause a delay that prevents the noise cancellation loop from cancelling high frequency sounds.
Accordingly, it would be useful to be able to perform active noise cancellation without needing a microphone to detect the ambient noise.